Search

Abstract Background Although adult mosquito vectors of sylvatic arbovirus [yellow fever (YFV), dengue-2 (DENV-2) and chikungunya (CHIKV)] have been studied for the past 40 years in southeastern Senegal, data are still lacking on the ecology of larval mosquitoes in this area. In this study, we investigated the larval habitats of mosquitoes and characterized their seasonal and spatial dynamics in arbovirus foci. Methods We searched for wet microhabitats, classified in 9 categories, in five land cover classes (agriculture, forest, savannah, barren and village) from June, 2010 to January, 2011. Mosquito immatures were sampled monthly in up to 30 microhabitats of each category per land cover and bred until adult stage for determination. Results No wet microhabitats were found in the agricultural sites; in the remaining land covers immature stages of 35 mosquito species in 7 genera were sampled from 9 microhabitats (tree holes, fresh fruit husks, decaying fruit husks, puddles, bamboo holes, discarded containers, tires, rock holes and storage containers). The most abundant species was Aedes aegypti formosus, representing 30.2% of the collections, followed by 12 species, representing each more than 1% of the total, among them the arbovirus vectors Ae. vittatus (7.9%), Ae. luteocephalus (5.7%), Ae. taylori (5.0%), and Ae. furcifer (1.3%). Aedes aegypti, Cx. nebulosus, Cx. perfuscus, Cx. tritaeniorhynchus, Er. chrysogster and Ae. vittatus were the only common species collected from all land covers. Aedes furcifer and Ae. taylori were collected in fresh fruit husks and tree holes. Species richness and dominance varied significantly in land covers and microhabitats. Positive associations were found mainly between Ae. furcifer, Ae. taylori and Ae. luteocephalus. A high proportion of potential enzootic vectors that are not anthropophilic were found in the larval mosquito fauna. Conclusions In southeastern Senegal, Ae. furcifer and Ae. taylori larvae showed a more limited distribution among both land cover and microhabitat types than the other common species. Uniquely among vector species, Ae. aegypti formosus larvae occurred at the highest frequency in villages. Finally, a high proportion of the potential non-anthropophilic vectors were represented in the larval mosquito fauna, suggesting the existence of unidentified sylvatic arbovirus cycles in southeastern Senegal.

Background: Chikungunya virus (CHIKV) originated in a sylvatic cycle of transmission between non-human animal hosts and vector mosquitoes in the forests of Africa. Subsequently the virus jumped out of this ancestral cycle into a human-endemic transmission cycle vectored by anthropophilic mosquitoes. Sylvatic CHIKV cycles persist in Africa and continue to spill over into humans, creating the potential for new CHIKV strains to enter human-endemic transmission. To mitigate such spillover, it is first necessary to delineate the distributions of the sylvatic mosquito vectors of CHIKV, to identify the environmental factors that shape these distributions, and to determine the association of mosquito presence with key drivers of virus spillover, including mosquito and CHIKV abundance. We therefore modeled the distribution of seven CHIKV mosquito vectors over two sequential rainy seasons in Kédougou, Senegal using Maxent. Methods: Mosquito data were collected in fifty sites distributed in five land cover classes across the study area. Environmental data representing land cover, topographic, and climatic factors were included in the models. Models were compared and evaluated using area under the receiver operating characteristic curve (AUROC) statistics. The correlation of model outputs with abundance of individual mosquito species as well as CHIKV-positive mosquito pools was tested. Results: Fourteen models were produced and evaluated; the environmental variables most strongly associated with mosquito distributions were distance to large patches of forest, landscape patch size, rainfall, and the normalized difference vegetation index (NDVI). Seven models were positively correlated with mosquito abundance and one (Aedes taylori) was consistently, positively correlated with CHIKV-positive mosquito pools. Eight models predicted high relative occurrence rates of mosquitoes near the villages of Tenkoto and Ngary, the areas with the highest frequency of CHIKV-positive mosquito pools. Conclusions: Of the environmental factors considered here, landscape fragmentation and configuration had the strongest influence on mosquito distributions. Of the mosquito species modeled, the distribution of Ae. taylori correlated most strongly with abundance of CHIKV, suggesting that presence of this species will be a useful predictor of sylvatic CHIKV presence. [ABSTRACT FROM AUTHOR]